OOS 4

Advances in Modeling Wildlife Abundance

Estimating population size has been a key issue of interest for decades in ecological studies. In conservation and management, some of the most pressing questions are related to how climate change and habitat fragmentation will impact populations. One major step in answering these questions is understanding the spatial and temporal dynamics of abundance, as well as, habitat associations, density dependence, and resource selection. Methods, such as capture-recapture, mark-resight, distance sampling, and aerial counts, are commonly used to estimate abundance for mammals, reptiles, birds, insects, trees, etc. New techniques such as genetic sampling and camera trapping, along with enhanced computing capabilities, have spurred a wave of advances in statistical models for abundance estimation. These extensions include explicitly incorporating spatial and temporal information, combining multiple data sources, investigating community structure, etc. These new approaches allow researchers to not only estimate abundance, but to address other ecological questions related to variation of abundance in space and time, survival/recruitment, animal movement, resource selection, and patterns in community composition. Modeling procedures that allow researchers to gain a better understanding of these processes are invaluable. For example, camera trapping now allows researchers to photo-capture animals that are cryptic or rare, such as jaguars. In some species, individuals can be identified in photo-captures and new spatial capture-recapture models can be utilized to estimate population size, variation in movement between sexes, resource selection, survival and recruitment. Similarly, with the use of new N-mixture models, repeated count data can be used to estimate population size and trends without having to identify individuals. In this session, we aim to provide an overview over a broad range of advances in models for estimating population size based on traditional methodologies like distance sampling, capture-recapture, and count based surveys, but incorporating new technologies and data sources to address questions broader than just abundance. The models are widely applicable across many taxa, time scales, and spatial extents in ecology.